Added Cauchy distribution verification tests.
git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@921479 13f79535-47bb-0310-9956-ffa450edef68
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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#------------------------------------------------------------------------------
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# R source file to validate Cauchy distribution tests in
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# org.apache.commons.math.distribution.CauchyDistributionTest
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#
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# To run the test, install R, put this file and testFunctions
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# into the same directory, launch R from this directory and then enter
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# source("<name-of-this-file>")
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#
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#-----------------------------------------------------------------------------
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tol <- 1E-9
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# Function definitions
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source("testFunctions") # utility test functions
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# function to verify distribution computations
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verifyDistribution <- function(points, expected, median, scale, tol) {
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rDistValues <- rep(0, length(points))
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i <- 0
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for (point in points) {
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i <- i + 1
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rDistValues[i] <- pcauchy(point, median, scale, log = FALSE)
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}
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output <- c("Distribution test median = ",median,", scale = ", scale)
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if (assertEquals(expected, rDistValues, tol, "Distribution Values")) {
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displayPadded(output, SUCCEEDED, WIDTH)
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} else {
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displayPadded(output, FAILED, WIDTH)
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}
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}
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# function to verify density computations
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verifyDensity <- function(points, expected, median, scale, tol) {
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rDensityValues <- rep(0, length(points))
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i <- 0
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for (point in points) {
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i <- i + 1
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rDensityValues[i] <- dcauchy(point, median, scale, log = FALSE)
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}
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output <- c("Density test median = ",median,", scale = ", scale)
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if (assertEquals(expected, rDensityValues, tol, "Density Values")) {
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displayPadded(output, SUCCEEDED, WIDTH)
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} else {
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displayPadded(output, FAILED, WIDTH)
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}
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}
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verifyQuantiles <- function(points, expected, median, scale, tol) {
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rQuantileValues <- rep(0, length(points))
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i <- 0
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for (point in points) {
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i <- i + 1
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rQuantileValues[i] <- qcauchy(point, median, scale, log = FALSE)
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}
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output <- c("Quantile test median = ",median,", scale = ", scale)
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if (assertEquals(expected, rQuantileValues, tol, "Quantile Values")) {
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displayPadded(output, SUCCEEDED, WIDTH)
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} else {
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displayPadded(output, FAILED, WIDTH)
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}
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}
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#--------------------------------------------------------------------------
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cat("Cauchy test cases\n")
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median <- 1.2
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scale <- 2.1
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distributionValues <- c(0.001, 0.01, 0.025, 0.05, 0.1, 0.999,
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0.990, 0.975, 0.950, 0.900)
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densityValues <- c(1.49599158008e-06, 0.000149550440335, 0.000933076881878, 0.00370933207799, 0.0144742330437,
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1.49599158008e-06, 0.000149550440335, 0.000933076881878, 0.00370933207799, 0.0144742330437)
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distributionPoints <- c(-667.24856187, -65.6230835029, -25.4830299460, -12.0588781808, -5.26313542807,
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669.64856187, 68.0230835029, 27.8830299460, 14.4588781808, 7.66313542807)
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verifyDistribution(distributionPoints, distributionValues, median, scale, tol)
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verifyDensity(distributionPoints, densityValues, median, scale, tol)
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verifyQuantiles(distributionValues, distributionPoints, median, scale, tol)
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displayDashes(WIDTH)
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